Modular Neural Network Learning Using Fuzzy Temporal Database
Despite the availability of several well-known neural network learning algorithms, we have taken the initiative to propose a new mechanism for initial learning and training of a neural network. Our methodology uses fuzzy temporal database as a storehouse of information that would be used to feed the network for learning and perfecting itself.
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- Bart Kosko, “Neural Networks And Fuzzy Systems”, Prentice Hall, 1992.Google Scholar
- Bart L.M. Happel and Jacob M.J. Murre, Design and Evolution of Modular Neural Architectures. Neural Networks, Vol. 7, No. 6/7, Pages 985 - 1004, 1994.Google Scholar
- C. J. Date, An Introduction to Database Systems, 7th edition, Pearson Education Asia Pte. Ltd, 2000.Google Scholar
- George J. Klir and Bo Yuan, Fuzzy sets and Fuzzy Logic: Theory and Application, Prentice Hall Inc., 1995.Google Scholar
- James A. Anderson and Edward Rosenfeld, Talking : An Oral History of Neural Networks, MIT Press, 2000.Google Scholar
- Laurene Fausett. Fundamentals of Neural Networks. Architectures, Algorithms, and Applications. Prentice-Hall. New Jersey, 1994.Google Scholar
- Mohamad H. Hassoun. Fundamentals of Artificial Neural Networks. Prentice Hall of India, 2002.Google Scholar
- Ramez Elmasri and Shamkant B. Navathe, Fundamentals of Database Systems, 3rd edition, Pearson Education Asia Pvt. Ltd., 2000.Google Scholar
- Shadab A. Siddiqui, Javed A. Alvi and A.Q. Ansari, A Generalised Fuzzy Temporal Database System With SQL Compatibility, 8th WSEAS Conference on Computers, pp. 222 – 226, 2004.Google Scholar
- Shadab A. Siddiqui, A.Q. Ansari and Shikha Agarwal, A Journey through Fuzzy Philosophy, PRANJANA, a Journal of Management Awareness, Vol. 6, No. 2, pp. 29 – 33, 2003.Google Scholar
- Simon Haykin. Neural Networks - A Comprehensive Foundation. New York, 1994.Google Scholar